code: def forward(self, x: torch.tensor, batch_index) -> torch.tensor:
      graph = ReadOut.divided_graph(x, batch_index)
  
      for i in range(len(graph)):
          graph[i] = graph[i].mean(dim=0).unsqueeze(0)
  
      out_readoout = torch.cat(graph, dim=0)
  
      return out_readoout
  
file_path: DIG/dig/xgraph/models/utils.py
imports: import torch
  from torch_geometric.utils.num_nodes import maybe_num_nodes
label_desc: Use image node_id 3 for calling the ReadOut obj's underlying member method code with example usage: obj.forward(x, batch_index) and returns: out_readoout